Research, Evals

Exa is building the search engine for the age of AI — from the silicon up. We run one of the most ambitious indexing operations in the world: crawling the open web at massive scale, training state-of-the-art embedding models to understand it, and powering everything through our own high-performance Rust-based vector database and a $5M H200 GPU cluster that regularly lights up tens of thousands of machines. The ML organization sits at the heart of this mission. We train foundational models for search. Our goal is to build systems that can instantly filter the world's knowledge to exactly what you want, no matter how complex your query. Basically, put the web into an extremely powerful database. And to do that well, we need to measure what “good search” actually means. That’s where you come in. We're looking for an ML evals engineer to design and build our eval stack at Exa. The role involves investigating how to evaluate search engines in an LLM world and then building the most compr